Akumulasi Regangan di Sumatera Berdasarkan Data Pengamatan GPS Tahun 2002-2008 dan Dampak Kerusakan Lingkungan Akibat Pelepasan Regangan

Pulau Sumatera terletak di antara dua lempeng tektonik yaitu lempeng Indo-Australia dan lempeng Eurasia. Intensitas gempa bumi sangat besar di pulau ini, terutama di sepanjang daerah pesisir barat. Pada 2002-2008 periode, banyak gempa bumi besar yang menyebabkan korban jiwa dan kerusakan lingkungan. Fenomena ini menunjukkan bahwa studi tentang pola deformasi pulau Sumatera sangat diperlukan. Studi yang diperlukan adalah untuk rencana mitigasi bencana di masa depan. Pola deformasi gempa dapat diamati dengan GPS pengamatan (Global Positioning System). Data yang digunakan untuk gempa Sumatera adalah GPS Sumatera Array (SuGAr). Perangkat lunak yang digunakan untuk data Array GPS Sumatera dari pulau Sumatera adalah Gamit 10.4. Dari hasil pengolahan data, dapat disimpulkan bahwa data perpindahan koordinat stasiun dapat digunakan jika data outlier telah terhapus. Dari koordinat perpindahan stasiun bisa diperoleh vektor perpindahan semua stasiun sebelum, selama atau setelah gempa bumi. Dari perpindahan nilai-nilai vektor, nilai regangan yang terjadi di sepanjang pulau Sumatera dapat diperkirakan. Dari data regangan, nilai akumulasi regangan 2002-2008 dapat diperoleh. Sehingga dapat dianalisis wilayah yang berpotensi terjadinya gempa selanjutnya

Earthquakes and tsunamis caused by low-angle normal faulting in the Banda Sea, Indonesia

As the world's largest archipelagic country in Earth's most active tectonic region, Indonesia faces a substantial earthquake and tsunami threat. Understanding this threat is a challenge because of the complex tectonic environment, the paucity of observed data and the limited historical record. Here we combine information from recent studies of the geology of Indonesia's Banda Sea with Global Positioning System observations of crustal motion and an analysis of historical large earthquakes and tsunamis there. We show that past destructive earthquakes were not caused by the supposed megathrust of the Banda outer arc as previously thought but are due to a vast submarine normal fault system recently discovered along the Banda inner arc. Instead of being generated by coseismic seafloor displacement, we find the tsunamis were more likely caused by earthquake-triggered submarine slumping along the fault's massive scarp, the Weber Deep. This would make the Banda detachment representative not only as a modern analogue for terranes hyper-extended by slab rollback but also for the generation of earthquakes and tsunamis by a submarine extensional fault system. Our findings suggest that low-angle normal faults in the Banda Sea generate large earthquakes, which in turn can generate tsunamis due to earthquake-triggered slumping. Low-angle normal faults in the Banda Sea have caused large earthquakes that indirectly generated tsunamis due to earthquake-triggered submarine slumping, according to an analysis of historical earthquake and tsunami events and GPS observations.Peer reviewe

Deformasi Koseismik Dan Pascaseismik Gempa YOGYAKARTA 2006 Dari Hasil Survei GPS

DOI: 10.17014/ijog.v4i4.87The Yogyakarta earthquake of 27 May 2006 occurred at 05:54 WIB with magnitude of 6.4 Mw. It shaked the region of Bantul, Yogyakarta, Sleman and Klaten for about 60 seconds. A week after the earthquake, i.e. 4-8 June 2006, a GPS survey was conducted on 48 GPS points belonging to the 2nd order national cadastral control network located in the earthquake affected region. The 2nd survey was conducted on 21-26 January 2008. The surveys were conducted using 14 dual-frequency geodetic type receivers and the Bernese 5.0 scientific software was used for data processing. The results of GPS surveys show that horizontal components of the co-seismic deformation of earthquake are generally about 10-15 cm or smaller. The GPS-derived displacement vectors and depths of aftershocks suggested the existence of left-lateral fault, with strike and dip angles of about 48o and 89o, located at about 5-10 km east of Opak Fault which is usually drawn along the Opak River. GPS surveys also estimate that horizontal components of the post-seismic deformation of Yogyakarta earthquake are about 0.3 to 9.1 cm between June 2006 and June 2008. While the co-seismic deformation shows the sinistral displacement, the post-seismic deformation indicates the dextral displacement of the eastern region of Opak Fault (Gunung Kidul area) which is relative to a more stable western region

Characteristic of Lokon Volcano Deformation of 2009 - 2011 Based on GPS Data

DOI: 10.17014/ijog.v7i4.147Precursor of Lokon Volcano eruptions in 2011 is believed to begin since December 2007 which was marked by increasing number of volcanic earthquakes and gas emission. To support this information, deformation method is used primarily to determine deformation characteristics of Lokon volcanic activity in the period of 2009-2011. The period of analysis is adapted to the presence of GPS data. Displacement rate of Lokon GPS observation points in the period of 2009 - 2011 ranged from 1.1 to 7 cm a year. Strain patterns that occur in the areas are compression surrounding Tompaluan crater and extension in the eastern slope. Location of the pressure source for August 2009 - March 2011 measurement was at a depth of 1800 m beneath Tompaluan crater. Deformation in the Lokon Volcano is characteristized by the compression zone in the summit and crater area caused by magma activity raised into the surface from a shallow magma source which is accompanied by a high release of volcanic gases. Accumulated pressure release and deformation rate as measured in the Lokon Volcano remain low

Crustal strain partitioning and the associated earthquake hazard in the eastern Sunda-Banda Arc

We use Global Positioning System (GPS) measurements of surface deformation to show that the convergence between the Australian Plate and Sunda Block in eastern Indonesia is partitioned between the megathrust and a continuous zone of back-arc thrusting extending 2000 km from east Java to north of Timor. Although deformation in this back-arc region has been reported previously, its extent and the mechanism of convergence partitioning have hitherto been conjectural. GPS observations establish that partitioning occurs via a combination of anticlockwise rotation of an arc segment called the Sumba Block, and left-lateral movement along a major NE-SW strike-slip fault west of Timor. We also identify a westward extension of the back-arc thrust for 300 km onshore into East Java, accommodating slip of ∼6 mm/yr. These results highlight a major new seismic threat for East Java and draw attention to the pronounced seismic and tsunami threat to Bali, Lombok, Nusa Tenggara, and other coasts along the Flores Sea

The Effects of Tropospheric Bias on Deformation Monitoring of MT. Guntur using GPS Survey Method

Pemantauan deformasi gunung api yang andal menuntut ketelitian yang tinggi, yaitu sampai level keteliatian mm untuk kasus gunung api yang tengah 'bangkit' kembali. Konsekuensinya adalah kesalahan dan bias yang dapat mengurangi ketelitian dalam penentuan posisi dengan satelit GPS harus dieliminasi dana tau direduksi, seperti kesalahan yang disebabkan oleh bias troposfer. Pada kasus pemantauan deformasi gunung api dengan metode survei GPS, karena adanya perbedaan tinggi yang cukup besar dan variatif antara titik-titik dalam jaringan, maka efek kesalahan bias troposfer tidak sepenuhnya dapat direduksi dengan proses pengurangan data (differencing). Residu (sisa) bias troposter ini harus dikoreksi agar tingkat keteliatian yang dituntut oleh sistem pemantauan deformasi gunung api dapat tetap tercapai. Pada makalah ini akan dibahas efek bias troposfer pada pemantauan deformasi gunung api. Pembahasan didasarkan pada hasil yang diperoleh dari pemantauan deformasi G. Guntur (Garut, Jawa Barat) dengan metode survei GPS. The Effects of Tropospheric Bias on Deformation Monitoring of MT. Guntur using GPS Survey MethodA reliable volcano deformation monitoring requires a high positioning accuracy, i.e. up to mm level in the case of reawakening volcanoes. As a consequence of this requirement, the errors and biases affecting the GPS positioning accuracy has to be eliminated or reduced, which one of them is the tropospheric bias. In the case of volcano deformation monitoring using the GPS survey method, due to a relatively large altitude variation in the stations altitude, the effects of tropospheric bias could not be effectively reduced by the differencing process. In order to meet the accuracy requirement of volcano deformation monitoring system, this residual tropospheric bias, therefore, has to be somehow corrected or taken into account. In this paper, the effects of tropospheric bias on the volcano deformation monitoring will be discussed. The discussion is based on the results from the deformation monitoring of Guntur volcano in Garut, West Java, by using repeated GPS surveys

SPATIAL ANALYSIS OF VOLCANIC ASH DISTRIBUTION DUE TO VOLCANIC ERUPTION IN JAVA ISLAND

Indonesia is located on the Ring of Fire with the most geologically active than any other countries, which makes it vulnerable due to the massive earthquakes and volcanic eruptions. Java Island has the most active volcano with high risks such as human risk and infrastructure from volcanic ash because of volcanic eruptions. The availability of the map of potential volcanic hazards is important to help mitigate the risk caused by volcanic eruptions. However, to the best of the author's knowledge, the distribution of volcanic ash has never been assessed in detail in the disaster-prone hazard map published by the Centre for Volcanology and Geological Hazard Mitigation (CVGHM), Indonesia. This research reported the potential distribution of volcanic ash due to volcanic eruptions in the future in Java island. Following the principles of Probabilistic Hazard Assessment and TephraProb software, the modeling of volcanic ash potential was performed using various parameters such as historical data, eruption source parameter, total grain-size distribution, tephra2 parameter, and the wind speed around the volcanoes as an input. The map shows the distribution of volcanic ash based on the volcanic ash accumulation (kg/m2) and the volcanic ash hazard map is classified into three classes. There are 19 models of volcanic ash distribution with various probabilities of exceedance based on 19 A-type volcanoes on Java Island. This volcano's distribution of volcanic ash tends to the southwest as the wind speed and direction